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Record W4417454632 · doi:10.1038/s41593-025-02143-6

Cold and lithium delay forgetting of olfactory memories in Caenorhabditis elegans

2025· article· en· W4417454632 on OpenAlexfundno aff
Dana Landschaft-Berliner, Kesem Goldstein, Guy Teichman, Sarit Anava, Hila Gingold, Yehuda Salzberg, Itai Rieger, Vladyslava Pechuk, Hagar Setty, Priti Agarwal, Dror Sagi, Dror Cohen, Evelina I. Nikelshparg, Anat Ben‐Zvi, Antonio Miranda‐Vizuete, Ronen Zaidel‐Bar, Meital Oren‐Suissa, Oded Rechavi

Bibliographic record

VenueNature Neuroscience · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersNational Institutes of HealthKreitman School of Advanced Graduate Studies, Ben-Gurion University of the NegevAzrieli FoundationDeutsche Forschungsgemeinschaft
KeywordsForgettingCaenorhabditis elegansOlfactory bulbDownregulation and upregulationMemory consolidationLithium (medication)SynapseInterneuron

Abstract

fetched live from OpenAlex

The persistence of memory reflects not only how it is formed but also how forgetting is delayed. The mechanisms controlling forgetting remain obscure, and in particular it is unclear to what degree this process is actively regulated. We discovered that cold exposure delays forgetting of specific olfactory memories by more than eight-fold and that adaptation to cold abolishes this effect. To study the underlying mechanism, we performed RNA sequencing, mutant analyses and pharmacological assays. Here we show that regulation of membrane properties underlies the presence and absence of cold-induced delayed forgetting. Furthermore, lithium can also delay forgetting in cold-sensitive worms but not in cold-tolerant worms; this effect involves downregulation of the diacylglycerol pathway in AWC neurons and long-term suppression of activity in the downstream AIY interneurons. Thus, the genetic tractability of worms might be harnessed to study the mechanism of action of lithium and cold exposure and, more fundamentally, how memory is stored and lost.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.240
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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